Papers
Learning from Corrupted Binary Labels via Class-Probability Estimation
Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong et al.
Learning from Data with Heterogeneous Noise using SGD
Shuang Song, Kamalika Chaudhuri, Anand Sarwate
Learning From Massive Noisy Labeled Data for Image Classification
Tong Xiao, Tian Xia, Yi Yang et al.
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Ozgur Simsek, Marcus Buckmann
Learning Graph Structure for Multi-Label Image Classification via Clique Generation
Mingkui Tan, Qinfeng Shi, Anton van den Hengel et al.
Learning Hypergraph-Regularized Attribute Predictors
Sheng Huang, Mohamed Elhoseiny, Ahmed Elgammal et al.
Learning Image and User Features for Recommendation in Social Networks
Xue Geng, Hanwang Zhang, Jingwen Bian et al.
Learning Image Representations Tied to Ego-Motion
Dinesh Jayaraman, Kristen Grauman
Learning Informative Edge Maps for Indoor Scene Layout Prediction
Arun Mallya, Svetlana Lazebnik
Learning Large-Scale Automatic Image Colorization
Aditya Deshpande, Jason Rock, David Forsyth
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
Gunwoong Park, Garvesh Raskutti
Learning Lightness From Human Judgement on Relative Reflectance
Takuya Narihira, Michael Maire, Stella X. Yu
Learning Like a Child: Fast Novel Visual Concept Learning From Sentence Descriptions of Images
Junhua Mao, Xu Wei, Yi Yang et al.
Learning Local Invariant Mahalanobis Distances
Ethan Fetaya, Shimon Ullman
Learning Multiple Visual Tasks While Discovering Their Structure
Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa
Learning Nonlinear Spectral Filters for Color Image Reconstruction
Michael Moeller, Julia Diebold, Guy Gilboa et al.
Learning of Non-Parametric Control Policies with High-Dimensional State Features
Herke Van Hoof, Jan Peters, Gerhard Neumann
Learning Ordinal Relationships for Mid-Level Vision
Daniel Zoran, Phillip Isola, Dilip Krishnan et al.
Learning Overcomplete Latent Variable Models through Tensor Methods
Animashree Anandkumar, Rong Ge, Majid Janzamin
Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding
Yongbo Li, Weisheng Dong, Guangming Shi et al.
Learning Parametric-Output HMMs with Two Aliased States
Roi Weiss, Boaz Nadler
Learning Program Embeddings to Propagate Feedback on Student Code
Chris Piech, Jonathan Huang, Andy Nguyen et al.
Learning Query and Image Similarities With Ranking Canonical Correlation Analysis
Ting Yao, Tao Mei, Chong-Wah Ngo
Learning Scale-Free Networks by Dynamic Node Specific Degree Prior
Qingming Tang, Siqi Sun, Jinbo Xu
Learning Scene-Specific Pedestrian Detectors Without Real Data
Hironori Hattori, Vishnu Naresh Boddeti, Kris M. Kitani et al.